Incorporate the power of Einstein in your Salesforce application About This Book ? Make better predictions of your business processes using prediction and predictive modeling ? Build your own custom models by leveraging PredictionIO on the Heroku platform ? Integrate Einstein into various cloud services to predict sales, marketing leads, insights into news feeds, and more Who This Book Is For This book is for developers, data scientists, and Salesforce-experienced consultants who want to explore Salesforce Einstein and its current offerings. It assumes some prior experience with the Salesforce platform. What You Will Learn ? Get introduced to AI and its role in CRM and cloud applications ? Understand how Einstein works for the sales, service, marketing, community, and commerce clouds ? Gain a deep understanding of how to use Einstein for the analytics cloud ? Build predictive apps on Heroku using PredictionIO, and work with Einstein Predictive Vision Services ? Incorporate Einstein in the IoT cloud ? Test the accuracy of Einstein through Salesforce reporting and Wave analytics In Detail Dreamforce 16 brought forth the latest addition to the Salesforce platform: an AI tool named Einstein. Einstein promises to provide users of all Salesforce applications with a powerful platform to help them gain deep insights into the data they work on. This book will introduce you to Einstein and help you integrate it into your respective business applications based on the Salesforce platform. We start off with an introduction to AI, then move on to look at how AI can make your CRM and apps smarter. Next, we discuss various out-of-the-box components added to sales, service, marketing, and community clouds from salesforce to add Artificial Intelligence capabilities. Further on, we teach you how to use Heroku, PredictionIO, and the force.com platform, along with Einstein, to build smarter apps. The core chapters focus on developer content and introduce PredictionIO and Salesforce Einstein Vision Services. We explore Einstein Predictive Vision Services, along with analytics cloud, the Einstein Data Discovery product, and IOT core concepts. Throughout the book, we also focus on how Einstein can be integrated into CRM and various clouds such as sales, services, marketing, and communities. By the end of the book, you will be able to embrace and leverage the power of Einstein, incorporating its functions to gain more knowledge. Salesforce developers will be introduced to the world of AI, while data scientists will gain insights into Salesforce’s various cloud offerings and how they can use Einstein’s capabilities and enhance applications. Style and approach This book takes a straightforward approach to explain Salesforce Einstein and all of its potential applications. Filled with examples, the book presents the facts along with seasoned advice and real-world use cases to ensure you have all the resources you need to incorporate the power of Einstein in your work.

This hands-on guide is aimed at practitioners of data science. The book assumes some previous skills with Julia and skills in coding in a *ing language such as Python or R, or a compiled language such as C or Java.

This book is for Elasticsearch users who want to extend their knowledge and develop new skills. Prior knowledge of the Query DSL and data indexing is expected.

If you are a developer who implements ElasticSearch in your web applications and want to sharpen your understanding of the core elements and applications, this is the book for you. It is assumed that you’ve got working knowledge of JSON and, if you want to extend ElasticSearch, of Java and related technologies.

This book focuses on readers starting their journey with Hyper-V, and assumes they have minimal or no knowledge of virtualization.

If you are a data analyst with basic knowledge of Big Data analysis but no knowledge of Splunk, then this book will help you get started with Splunk. The book assumes that you have access to a copy of Splunk, ideally not in production, and many examples also assume you have administrator rights.

This book is written in a clear conversational style, which emphasizes a practical learn-by-doing approach. This step by step guide has illustrative examples to implement Ext JS library features in your Oracle APEX applications If you are an Oracle APEX application developer who wants to take APEX applications to the next level by taking advantage of Ext JS features, this book is for you. Prior knowledge of Oracle APEX is required, however, no prior knowledge of Ext JS is required.

Written in a stepbystep, tutorial style with a lot of code snippets and handson examples to create an advanced Magento theme from scratch, this book is tailormade for web designers and developers. This book is great for developers and web designers who are looking to get a good grounding in how to create custom, responsive, and advanced Magento themes. Readers must have some experience with HTML, PHP, CSS, and Magento theme design. This book will be useful for anybody who already has knowledge of the Magento frontend structure.

A comprehensive practical guide that walks you through the multiple stages of data management in enterprise and gives you numerous design patterns with appropriate code examples to solve frequent problems in each of these stages. The chapters are organized to mimick the sequential data flow evidenced in Analytics platforms, but they can also be read independently to solve a particular group of problems in the Big Data life cycle. If you are an experienced developer who is already familiar with Pig and is looking for a use case standpoint where they can relate to the problems of data ingestion, profiling, cleansing, transforming, and egressing data encountered in the enterprises. Knowledge of Hadoop and Pig is necessary for readers to grasp the intricacies of Pig design patterns better.

This book is written in an easytounderstand style, following an enterprise development process through all the phases of development and deployment. Concepts are illustrated with realworld examples and the methods used are explained stepbystep. This book is for Oracle developers looking to start using Oracle’s latest development tool and J2EE developers looking for a more productive way to build modern web applications. This book will guide you through the creation of a successful enterprise application with Oracle ADF 12c, and therefore it assumes you have basic knowledge of Java, JDeveloper, and databases.

Throughout the book, we will follow a fictional company, the case study will help you in implementing FIM 2010 R2. All the examples in the book will relate to this fictive company and you will be taken from design, to installation, to configuration of FIM 2010 R2. If you are implementing and managing FIM 2010 R2 in your business, then this book is for you. You will need to have a basic understanding of Microsoft based infrastructure using Active Directory. If you are new to Forefront Identity Management, the case-study approach of this book will help you to understand the concepts and implement them.

A practical tutorial containing clear, step-by-step explanations of all the concepts required to understand the technology involved in virtualizing your application infrastructure. Each chapter uses real-world scenarios so that the readers can put into practice what they learn immediately and with the right guidance. Each topic is written defining a common need and developing the process to solve it using Microsoft App-V. This book is for system administrators or consultants who want to master and dominate App-V, and gain a deeper understanding of the technology in order to optimize App V implementations. Even though the book does not include basic steps like installing App-V components or sequencing simple applications; application virtualization beginners will receive a comprehensive look into App-V before jumping into the technical process of each chapter.

This book will help beginners to create stylish and professional looking dashboards in no time. It is also intended for BI developers who want to use SAP BO to facilitate BI in their organizations. No prior knowledge is required, however, you must have a basic knowledge of MS Excel and some analytical skills to build expressive business charts.

This book is intended for middleware system administrators and Java developers, actually good Java developers, who care about architecture design and implementation. Whether you are new to WildFly, come from a previous version, such as JBoss AS 5, 6, and 7, or are an expert in it, you will be able to master both the basic and advanced features of WildFly. By the way, most of the core components of WildFly are totally new, such as its administration tool, that is, the CLI; its operational modes, which are, the standalone and domain modes; and its web server provided by Undertow, you can benefit from this book even if you have no experience in JBoss and WildFly at all.

This is a practical guide providing comprehensive solutions for SQL query problems, and is full of concrete real-world examples to help you create and troubleshoot your SQL queries in SAP Business One. If you are a system administrator who uses SQL query as your tool of choice for solving specific problems throughout SAP Business One, then this book is for you. It may also be useful if you are a developer or consultant using this technology, and can benefit end users by improving your search for important business information. A rudimentary knowledge of SAP Business One and SQL Server is required to use this book efficiently. Examples covered are relevant to SBO 2007A users, for which the 8.8 release is mostly compatible. All SQL query examples within the book are verified under SQL Server 2005, so they are guaranteed to run under this release, in addition to SQL Server 2008. Non-SAP Business One users can also gain knowledge from the many examples throughout the book. It is hard to find another book with so many SQL query examples.

You will be led carefully stepbystep through a detailed set of recipes. This book focuses on web content management using Microsoft SharePoint 2013 server. The practical examples are built logically throughout the chapters to create a common theme. This book is ideal for developers who want to broaden their understanding of the web content management features available with SharePoint 2013. It is assumed that you already have some experience using SharePoint and developing web content. Experience with Microsoft PowerShell and coding C# with Visual Studio will also be helpful, but is not essential.

Load, wrangle, and analyze your data using the world's most powerful statistical programming language About This Book Load, manipulate and analyze data from different sources Gain a deeper understanding of fundamentals of applied statistics A practical guide to performing data analysis in practice Who This Book Is For Whether you are learning data analysis for the first time, or you want to deepen the understanding you already have, this book will prove to an invaluable resource. If you are looking for a book to bring you all the way through the fundamentals to the application of advanced and effective analytics methodologies, and have some prior programming experience and a mathematical background, then this is for you. What You Will Learn Navigate the R environment Describe and visualize the behavior of data and relationships between data Gain a thorough understanding of statistical reasoning and sampling Employ hypothesis tests to draw inferences from your data Learn Bayesian methods for estimating parameters Perform regression to predict continuous variables Apply powerful classification methods to predict categorical data Handle missing data gracefully using multiple imputation Identify and manage problematic data points Employ parallelization and Rcpp to scale your analyses to larger data Put best practices into effect to make your job easier and facilitate reproducibility In Detail Frequently the tool of choice for academics, R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. With over 7,000 user contributed packages, it’s easy to find support for the latest and greatest algorithms and techniques. Starting with the basics of R and statistical reasoning, Data Analysis with R dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. Packed with engaging problems and exercises, this book begins with a review of R and its syntax. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with “messy data”, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst. Style and approach Learn data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach.

Master machine learning techniques with R to deliver insights for complex projectsAbout This BookGet to grips with the application of Machine Learning methods using an extensive set of R packagesUnderstand the benefits and potential pitfalls of using machine learning methodsImplement the numerous powerful features offered by R with this comprehensive guide to building an independent R-based ML system Who This Book Is For If you want to learn how to use R's machine learning capabilities to solve complex business problems, then this book is for you. Some experience with R and a working knowledge of basic statistical or machine learning will prove helpful.What You Will LearnGain deep insights to learn the applications of machine learning tools to the industryManipulate data in R efficiently to prepare it for analysisMaster the skill of recognizing techniques for effective visualization of dataUnderstand why and how to create test and training data sets for analysisFamiliarize yourself with fundamental learning methods such as linear and logistic regressionComprehend advanced learning methods such as support vector machinesRealize why and how to apply unsupervised learning methods In Detail Machine learning is a field of Artificial Intelligence to build systems that learn from data. Given the growing prominence of R—a cross-platform, zero-cost statistical programming environment—there has never been a better time to start applying machine learning to your data. The book starts with introduction to Cross-Industry Standard Process for Data Mining. It takes you through Multivariate Regression in detail. Moving on, you will also address Classification and Regression trees. You will learn a couple of “Unsupervised techniques”. Finally, the book will walk you through text analysis and time series. The book will deliver practical and real-world solutions to problems and variety of tasks such as complex recommendation systems. By the end of this book, you will gain expertise in performing R machine learning and will be able to build complex ML projects using R and its packages.Style and approach This is a book explains complicated concepts with easy to follow theory and real-world, practical applications. It demonstrates the power of R and machine learning extensively while highlighting the constraints.

Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization About This Book Handle your data with precision and care for optimal business intelligence Restructure and transform your data to inform decision-making Packed with practical advice and tips to help you get to grips with data mining Who This Book Is For If you are a data scientist or R developer who wants to explore and optimize your use of R’s advanced features and tools, this is the book for you. A basic knowledge of R is required, along with an understanding of database logic. What You Will Learn Connect to and load data from R’s range of powerful databases Successfully fetch and parse structured and unstructured data Transform and restructure your data with efficient R packages Define and build complex statistical models with glm Develop and train machine learning algorithms Visualize social networks and graph data Deploy supervised and unsupervised classification algorithms Discover how to visualize spatial data with R In Detail R is an essential language for sharp and successful data analysis. Its numerous features and ease of use make it a powerful way of mining, managing, and interpreting large sets of data. In a world where understanding big data has become key, by mastering R you will be able to deal with your data effectively and efficiently. This book will give you the guidance you need to build and develop your knowledge and expertise. Bridging the gap between theory and practice, this book will help you to understand and use data for a competitive advantage. Beginning with taking you through essential data mining and management tasks such as munging, fetching, cleaning, and restructuring, the book then explores different model designs and the core components of effective analysis. You will then discover how to optimize your use of machine learning algorithms for classification and recommendation systems beside the traditional and more recent statistical methods. Style and approach Covering the essential tasks and skills within data science, Mastering Data Analysis provides you with solutions to the challenges of data science. Each section gives you a theoretical overview before demonstrating how to put the theory to work with real-world use cases and hands-on examples.

Leverage the power of Scala with different tools to build scalable, robust data science applicationsAbout This BookA complete guide for scalable data science solutions, from data ingestion to data visualizationDeploy horizontally scalable data processing pipelines and take advantage of web frameworks to build engaging visualizationsBuild functional, type-safe routines to interact with relational and NoSQL databases with the help of tutorials and examples providedWho This Book Is ForIf you are a Scala developer or data scientist, or if you want to enter the field of data science, then this book will give you all the tools you need to implement data science solutions.What You Will LearnTransform and filter tabular data to extract features for machine learningImplement your own algorithms or take advantage of MLLib’s extensive suite of models to build distributed machine learning pipelinesRead, transform, and write data to both SQL and NoSQL databases in a functional mannerWrite robust routines to query web APIsRead data from web APIs such as the GitHub or Twitter APIUse Scala to interact with MongoDB, which offers high performance and helps to store large data sets with uncertain query requirementsCreate Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizationsDeploy scalable parallel applications using Apache Spark, loading data from HDFS or HiveIn DetailScala is a multi-paradigm programming language (it supports both object-oriented and functional programming) and *ing language used to build applications for the JVM. Languages such as R, Python, Java, and so on are mostly used for data science. It is particularly good at analyzing large sets of data without any significant impact on performance and thus Scala is being adopted by many developers and data scientists. Data scientists might be aware that building applications that are truly scalable is hard. Scala, with its powerful functional libraries for interacting with databases and building scalable frameworks will give you the tools to construct robust data pipelines.This book will introduce you to the libraries for ingesting, storing, manipulating, processing, and visualizing data in Scala.Packed with real-world examples and interesting data sets, this book will teach you to ingest data from flat files and web APIs and store it in a SQL or NoSQL database. It will show you how to design scalable architectures to process and modelling your data, starting from simple concurrency constructs such as parallel collections and futures, through to actor systems and Apache Spark. As well as Scala’s emphasis on functional structures and immutability, you will learn how to use the right parallel construct for the job at hand, minimizing development time without compromising scalability. Finally, you will learn how to build beautiful interactive visualizations using web frameworks.This book gives tutorials on some of the most common Scala libraries for data science, allowing you to quickly get up to speed with building data science and data engineering solutions.Style and approachA tutorial with complete examples, this book will give you the tools to start building useful data engineering and data science solutions straightaway

Learn Database design, development,and administration using the feature-rich SQL Developer 4.1 interfaceAbout This BookExplore all the SQL Developer 4.1 features useful for Oracle database developers, architects, and administratorsUnderstand how this free tool from Oracle has evolved over the years and has become a complete tool that makes life easy for Oracle and third-party database usersThe author, Ajith Narayanan, has a total of 10+ years of work experience as an Oracle [APPS] DBAWho This Book Is ForThis book is intended for Oracle developers who are responsible for database management. You are expected to have programming knowledge of SQL and PL/SQL, and must be familiar with basic Oracle database concepts.What You Will LearnInstall and navigate through all the advanced features of SQL Developer that were introduced in version 4.1Browse, create, edit, and delete (drop) database objectsUse the SQL worksheet to run SQL statements and *s, edit and debug PL/SQL code, manipulate and export (unload) dataCarry out all DBA-related activities such as exporting/importing, tuning, and analyzing database performance issuesQuickly analyze, create, and edit the data model using data modelerExtend the SQL developer capabilities by exploring the APEX related pages, enabling and working with RESTful servicesUse the available reports and create new custom reports with custom *sGrasp how to connect to third-party databases and work smoothly with themIn DetailAt times, DBAs support 100s of databases at work. In such scenarios, using a command-line tool like putty adds to the difficulty, while SQL Developer makes the life of a developer, DBA, or DB architect easier by providing a graphical user interface equipped with features that can bolster and enhance the user experience and boost efficiency. Features such as DBA panel, Reports, Data Modeler, and Data Miner are just a few examples of its rich features, and its support for APEX, REST Services, timesten, and third-party database drivers demonstrate its extensibility.You may be a newbie to databases or a seasoned database expert, either way this book will help you understand the database structure and the different types of objects that organize enterprise data in an efficient manner. This book introduces the features of the SQL Developer 4.1 tool in an incremental fashion, starting with installing them, making the database connections, and using the different panels. By sequentially walking through the steps in each chapter, you will quickly master SQL Developer 4.1.Style and approachThis book follows a step-by-step approach and is in a conversational and easy-to-follow style. Screenshots , and detailed explanations of the basic and advanced features of SQL Developer 4.1 that will make your work and life easy.